4.7 Article

Interactive Artificial Intelligence Meets Game Theory in Next-Generation Communication Networks

Journal

IEEE WIRELESS COMMUNICATIONS
Volume 28, Issue 2, Pages 128-135

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/MWC.001.1800554

Keywords

Game theory; Games; Artificial intelligence; Resource management; Interference; Device-to-device communication; Communication networks

Funding

  1. National Key Research and Development Program of China [2020YFB1807700]
  2. National Science Foundation of China [61871454]
  3. Science and Technology on Communication Networks Laboratory, Shijiazhuang, Hebei, China [SXX19641X073]
  4. Aeronautical Science Foundation of China [ASFC-2018ZG81002]

Ask authors/readers for more resources

This article discusses the challenges in next-generation communication networks and proposes a novel framework combining machine learning and game theory to address the network selection problem in 5G ultra-dense and heterogeneous networks, resulting in reduced average delay for users.
Next-generation communication networks can provide high capacity, low latency, and massive connections; however, they introduce novel challenges of management complexity, and traditional mathematical methods cannot well characterize the rational behavior of users. In this article, we pay attention to the methods of artificial intelligence (AI) and game theory. We first review the applications of machine learning (ML) and game theory models in wireless communications and summarize their advantages and disadvantages. After surveying the state of the art, in this article we propose a novel framework combining ML and game theory, which explores and exploits the benefits of the two disciplines. Finally, we apply our novel framework to solve the network selection problem in a 5G ultra-dense and heterogeneous network. Simulation results confirm the advantage of our presented framework on reducing the average delay of users.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available